{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T06:56:15Z","timestamp":1781592975365,"version":"3.54.5"},"reference-count":56,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/100017724","name":"Henan Provincial Department of Transportation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100017724","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012659","name":"Foundation for Innovative Research Groups of the National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012659","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Engineering Applications of Artificial Intelligence"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.engappai.2026.115137","type":"journal-article","created":{"date-parts":[[2026,5,22]],"date-time":"2026-05-22T02:57:27Z","timestamp":1779418647000},"page":"115137","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"P1","title":["Automatic identification method for phase structure of steel slag concrete based on deep learning network of transformer"],"prefix":"10.1016","volume":"179","author":[{"given":"Chao","family":"Yin","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guanting","family":"Ye","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3876-2436","authenticated-orcid":false,"given":"Qing","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Donglin","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.engappai.2026.115137_bib1","series-title":"ACI 211.1-91: Standard Practice for Selecting Proportions for Normal, Heavyweight, and Mass Concrete","year":"1991"},{"issue":"8","key":"10.1016\/j.engappai.2026.115137_bib2","doi-asserted-by":"crossref","first-page":"2476","DOI":"10.3390\/buildings14082476","article-title":"Data-driven predictive modeling of steel slag concrete strength for sustainable construction","volume":"14","author":"Al-Hamd","year":"2024","journal-title":"Buildings"},{"key":"10.1016\/j.engappai.2026.115137_bib3","doi-asserted-by":"crossref","DOI":"10.1016\/j.conbuildmat.2021.123910","article-title":"Mechanical performance and resistance to carbonation of steel slag reinforced concrete","volume":"298","author":"Andrade","year":"2021","journal-title":"Constr. Build. Mater."},{"key":"10.1016\/j.engappai.2026.115137_bib4","doi-asserted-by":"crossref","first-page":"1971","DOI":"10.28991\/CEJ-2023-09-08-011","article-title":"Optimizing the flexural behavior of bamboo reinforced concrete beams containing cassava peel ash using response surface methodology","volume":"9","author":"Awolusi","year":"2023","journal-title":"Civ. Eng."},{"key":"10.1016\/j.engappai.2026.115137_bib5","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1007\/s41062-025-01973-4","article-title":"Evaluating the compressive strength of fly ash-slag-based geopolymer concrete: impact of hydraulic, silica, alumina, and lime moduli, and sodium silicate using various predictive models","volume":"10","author":"Baqer","year":"2025","journal-title":"Innov. Infrastruct. Solut."},{"key":"10.1016\/j.engappai.2026.115137_bib6","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"14496","article-title":"FlexiViT: one model for all patch sizes","author":"Beyer","year":"2023"},{"key":"10.1016\/j.engappai.2026.115137_bib7","doi-asserted-by":"crossref","DOI":"10.1016\/j.cemconcomp.2021.104153","article-title":"An experimental and numerical investigation of coarse aggregate settlement in fresh concrete under vibration","volume":"122","author":"Cai","year":"2021","journal-title":"Cement Concr. Compos."},{"issue":"1","key":"10.1016\/j.engappai.2026.115137_bib8","doi-asserted-by":"crossref","first-page":"812","DOI":"10.1038\/s41597-023-02734-7","article-title":"Automatic segmentation framework of X-ray tomography data for multi-phase rock using Swin transformer approach","volume":"10","author":"Chen","year":"2023","journal-title":"Sci. Data"},{"issue":"1","key":"10.1016\/j.engappai.2026.115137_bib9","first-page":"123","article-title":"Deep learning-based segmentation model for permeable concrete meso-structures","volume":"39","author":"Chen","year":"2024","journal-title":"Comput. Aided Civ. Infrastruct. Eng."},{"key":"10.1016\/j.engappai.2026.115137_bib10","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2025.110758","article-title":"Real-time asphalt pavement ice detection and annotation with a Transformer-based model framework","volume":"152","author":"Chen","year":"2025","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"2","key":"10.1016\/j.engappai.2026.115137_bib11","doi-asserted-by":"crossref","first-page":"944","DOI":"10.3390\/su13020521","article-title":"Sustainable recycling of electric arc furnace steel slag as aggregate in concrete: effects on the environmental and technical performance","volume":"13","author":"Diotti","year":"2021","journal-title":"Sustainability"},{"key":"10.1016\/j.engappai.2026.115137_bib12","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.110962","article-title":"Dual-scale enhanced and cross-generative consistency learning for semi-supervised medical image segmentation","volume":"158","author":"Gu","year":"2025","journal-title":"Pattern Recogn."},{"key":"10.1016\/j.engappai.2026.115137_bib13","doi-asserted-by":"crossref","DOI":"10.1016\/j.conbuildmat.2022.127033","article-title":"Online measurement and segmentation algorithm of coarse aggregate based on deep learning and experimental comparison","volume":"327","author":"Hu","year":"2022","journal-title":"Constr. Build. Mater."},{"key":"10.1016\/j.engappai.2026.115137_bib14","article-title":"Analyzing the pore structure of pervious concrete based on the deep learning framework of mask R-CNN","volume":"311","author":"Hua","year":"2021","journal-title":"Constr. Build. Mater."},{"key":"10.1016\/j.engappai.2026.115137_bib15","article-title":"Improving the post-fire behaviour of steel slag coarse aggregate concrete by adding GGBFS","volume":"74","author":"Huang","year":"2023","journal-title":"J. Build. Eng."},{"key":"10.1016\/j.engappai.2026.115137_bib16","doi-asserted-by":"crossref","DOI":"10.1016\/j.conbuildmat.2025.141008","article-title":"Packing coupled post-fire behavior of ultra-heavy-weight concrete","volume":"477","author":"Huang","year":"2025","journal-title":"Constr. Build. Mater."},{"key":"10.1016\/j.engappai.2026.115137_bib17","doi-asserted-by":"crossref","first-page":"185","DOI":"10.21834\/ajqol.v3i9.89","article-title":"Toward sustainable construction: use of recycled aggregate in concrete in Malaysia","volume":"3","author":"Ismail","year":"2018","journal-title":"Asian J. Qual. Life"},{"key":"10.1016\/j.engappai.2026.115137_bib18","doi-asserted-by":"crossref","DOI":"10.1109\/TGRS.2025.3543556","article-title":"Hypergraph BiFormer for semantic segmentation of high-resolution remote sensing images","volume":"63","author":"Jing","year":"2025","journal-title":"IEEE Trans. Geosci. Rem. Sens."},{"key":"10.1016\/j.engappai.2026.115137_bib19","doi-asserted-by":"crossref","first-page":"166","DOI":"10.28991\/HEF-2023-04-02-03","article-title":"Recycled concrete aggregates: a promising and sustainable option for the construction industry","volume":"4","author":"Kryeziu","year":"2023","journal-title":"Human Earth and Future"},{"key":"10.1016\/j.engappai.2026.115137_bib20","doi-asserted-by":"crossref","first-page":"3845","DOI":"10.3390\/app12083845","article-title":"Structural damage prediction of a reinforced concrete frame under single and multiple seismic events using machine learning algorithms","volume":"12","author":"Lazaridis","year":"2022","journal-title":"Appl. Sci."},{"key":"10.1016\/j.engappai.2026.115137_bib21","first-page":"3357","article-title":"Influence of the steel slag particle size on the mechanical properties and microstructure of concrete","volume":"16","author":"Li","year":"2024","journal-title":"Sustainability"},{"key":"10.1016\/j.engappai.2026.115137_bib22","article-title":"Automatic crack detection on concrete and asphalt surfaces using semantic segmentation network with hierarchical transformer","volume":"301","author":"Li","year":"2024","journal-title":"Eng. Struct."},{"key":"10.1016\/j.engappai.2026.115137_bib23","doi-asserted-by":"crossref","DOI":"10.1016\/j.autcon.2024.105440","article-title":"CNN-transformer hybrid network for concrete dam crack patrol inspection","volume":"163","author":"Li","year":"2024","journal-title":"Autom. ConStruct."},{"key":"10.1016\/j.engappai.2026.115137_bib24","article-title":"Microstructure-informed deep learning model for accurate prediction of multiple concrete properties","volume":"98","author":"Li","year":"2024","journal-title":"J. Build. Eng."},{"key":"10.1016\/j.engappai.2026.115137_bib25","doi-asserted-by":"crossref","DOI":"10.1016\/j.conbuildmat.2023.132766","article-title":"A new method for evaluating the uniformity of steel slag distribution in steel slag asphalt mixture based on deep learning","volume":"400","author":"Liu","year":"2023","journal-title":"Constr. Build. Mater."},{"key":"10.1016\/j.engappai.2026.115137_bib26","series-title":"JGJ 55-2011: Specification for Mix Proportion Design of Ordinary Concrete","year":"2011"},{"key":"10.1016\/j.engappai.2026.115137_bib27","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1007\/s41062-024-01464-y","article-title":"Utilization of steel slag as partial replacement for coarse aggregate in concrete","volume":"9","author":"Mitwally","year":"2024","journal-title":"Innov. Infrastruct. Solut."},{"key":"10.1016\/j.engappai.2026.115137_bib28","article-title":"Factors affecting compressive strength of steel slag concrete: a systematic literature review","volume":"86","author":"Nguyen","year":"2025","journal-title":"J. Build. Eng."},{"key":"10.1016\/j.engappai.2026.115137_bib29","doi-asserted-by":"crossref","first-page":"1491","DOI":"10.28991\/CEJ-2023-09-06-015","article-title":"The influence of climatic aging on the performance of wood-based panels","volume":"9","author":"Pakhomova","year":"2023","journal-title":"Civ. Eng."},{"issue":"45","key":"10.1016\/j.engappai.2026.115137_bib30","doi-asserted-by":"crossref","first-page":"68488","DOI":"10.1007\/s11356-022-20518-1","article-title":"Electrical conductivity, microstructures, chemical compositions, and systematic multivariable models to evaluate the effect of waste slag smelting (pyrometallurgical) on the compressive strength of concrete","volume":"29","author":"Piro","year":"2022","journal-title":"Environ. Sci. Pollut. Control Ser."},{"issue":"2","key":"10.1016\/j.engappai.2026.115137_bib31","doi-asserted-by":"crossref","first-page":"2093","DOI":"10.1002\/suco.202200023","article-title":"Multifunctional computational models to predict the long-term compressive strength of concrete incorporated with waste steel slag","volume":"24","author":"Piro","year":"2023","journal-title":"Struct. Concr."},{"key":"10.1016\/j.engappai.2026.115137_bib32","doi-asserted-by":"crossref","DOI":"10.1016\/j.conbuildmat.2019.117605","article-title":"Vertical distribution of pore-aggregate cement paste in statically compacted pervious concrete","volume":"237","author":"Rao","year":"2020","journal-title":"Constr. Build. Mater."},{"key":"10.1016\/j.engappai.2026.115137_bib33","article-title":"Properties of concrete containing electric arc furnace steel slag and steel sludge","volume":"25","author":"Roslan","year":"2019","journal-title":"J. Build. Eng."},{"key":"10.1016\/j.engappai.2026.115137_bib34","article-title":"Evaluation of conductive concrete made with steel slag aggregates","volume":"317","author":"Santill\u00e1n","year":"2022","journal-title":"Constr. Build. Mater."},{"key":"10.1016\/j.engappai.2026.115137_bib35","doi-asserted-by":"crossref","first-page":"4846","DOI":"10.1007\/s12205-019-0700-3","article-title":"The efficiency of steel slag and recycled concrete aggregate on the strength properties of concrete","volume":"23","author":"Sharba","year":"2019","journal-title":"KSCE J. Civ. Eng."},{"key":"10.1016\/j.engappai.2026.115137_bib36","article-title":"Weakly supervised deep learning-based concrete aggregates automatic segmentation for assessing separation degree","volume":"82","author":"Shi","year":"2024","journal-title":"J. Build. Eng."},{"key":"10.1016\/j.engappai.2026.115137_bib37","article-title":"Adopting an image analysis method to study the influence of segregation on the compressive strength of lightweight aggregate concretes","volume":"323","author":"Solak","year":"2022","journal-title":"Constr. Build. Mater."},{"key":"10.1016\/j.engappai.2026.115137_bib38","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-023-37676-y","article-title":"ConvNeXt steel slag sand substitution rate detection method incorporating attention mechanism","volume":"13","author":"Teng","year":"2023","journal-title":"Sci. Rep."},{"issue":"6","key":"10.1016\/j.engappai.2026.115137_bib39","doi-asserted-by":"crossref","first-page":"1178","DOI":"10.1080\/19648189.2024.2431740","article-title":"Effect evaluation and mechanism analysis of steel slag fine aggregate on the strengths of recycled aggregate concretes","volume":"29","author":"Tian","year":"2025","journal-title":"Eur. J. Environ. Civil Eng."},{"key":"10.1016\/j.engappai.2026.115137_bib40","article-title":"Automatic concrete crack segmentation model based on transformer","volume":"142","author":"Wang","year":"2022","journal-title":"Autom. ConStruct."},{"key":"10.1016\/j.engappai.2026.115137_bib41","doi-asserted-by":"crossref","DOI":"10.1016\/j.autcon.2021.104106","article-title":"Automatic segmentation of concrete aggregate using convolutional neural network","volume":"134","author":"Wang","year":"2022","journal-title":"Autom. ConStruct."},{"key":"10.1016\/j.engappai.2026.115137_bib42","article-title":"YOLOv8-CDD: an improved concrete defect detection method combined CNN with transformer","volume":"36","author":"Wang","year":"2024","journal-title":"Meas. Sci. Technol."},{"issue":"11","key":"10.1016\/j.engappai.2026.115137_bib43","doi-asserted-by":"crossref","first-page":"1817","DOI":"10.3390\/buildings15111817","article-title":"Stress-strain prediction for steam-cured steel slag fine aggregate concrete based on machine learning algorithms","volume":"15","author":"Wang","year":"2025","journal-title":"Buildings"},{"key":"10.1016\/j.engappai.2026.115137_bib44","article-title":"Macro and mesoscopic mechanical behavior of concrete with actual aggregate segmented by hybrid Transformers and convolutional neural networks","volume":"22","author":"Wang","year":"2025","journal-title":"Case Stud. Constr. Mater."},{"key":"10.1016\/j.engappai.2026.115137_bib45","article-title":"Macroscopic mechanical properties and microstructure characteristics of steel slag fine aggregate concrete","volume":"56","author":"Xue","year":"2022","journal-title":"J. Build. Eng."},{"key":"10.1016\/j.engappai.2026.115137_bib46","article-title":"Autonomous surface crack identification of concrete structures based on the YOLOv7 algorithm","volume":"73","author":"Ye","year":"2023","journal-title":"J. Build. Eng."},{"key":"10.1016\/j.engappai.2026.115137_bib47","article-title":"Evaluation method for uniformity of steel slag concrete aggregate based on improved YOLOv8","volume":"98","author":"Ye","year":"2024","journal-title":"J. Build. Eng."},{"key":"10.1016\/j.engappai.2026.115137_bib48","doi-asserted-by":"crossref","first-page":"687","DOI":"10.1016\/j.conbuildmat.2018.12.135","article-title":"Study on the pores characteristics and permeability simulation of pervious concrete based on 2d\/3d CT images","volume":"200","author":"Yu","year":"2019","journal-title":"Constr. Build. Mater."},{"issue":"2","key":"10.1016\/j.engappai.2026.115137_bib49","first-page":"682","article-title":"Pore structure identification method for pervious concrete based on improved U-Net and fusion algorithm","volume":"27","author":"Yu","year":"2023","journal-title":"KSCE J. Civ. Eng."},{"key":"10.1016\/j.engappai.2026.115137_bib50","article-title":"Automatic identification method for three-phase structure of pervious concrete based on deep learning network of Mask R-CNN","volume":"411","author":"Yu","year":"2024","journal-title":"Constr. Build. Mater."},{"issue":"22","key":"10.1016\/j.engappai.2026.115137_bib51","first-page":"3826","article-title":"YOLOv5-Ytiny: a miniature aggregate detection","volume":"11","author":"Yuan","year":"2022","journal-title":"Electronics"},{"issue":"22","key":"10.1016\/j.engappai.2026.115137_bib52","doi-asserted-by":"crossref","first-page":"3483","DOI":"10.1111\/mice.13523","article-title":"Adaptive feature expansion and fusion model for precast component segmentation","volume":"40","author":"Yuen","year":"2025","journal-title":"Comput. Aided Civ. Infrastruct. Eng."},{"key":"10.1016\/j.engappai.2026.115137_bib53","article-title":"Enhanced concrete crack detection and proactive safety warning based on I-ST-UNet model","volume":"159","author":"Zhang","year":"2024","journal-title":"Autom. ConStruct."},{"key":"10.1016\/j.engappai.2026.115137_bib54","doi-asserted-by":"crossref","DOI":"10.1016\/j.conbuildmat.2025.141488","article-title":"Deep learning-enhanced nonlinear ultrasonic identification of concrete micro crack development","volume":"479","author":"Zhao","year":"2025","journal-title":"Constr. Build. Mater."},{"key":"10.1016\/j.engappai.2026.115137_bib55","doi-asserted-by":"crossref","DOI":"10.1016\/j.conbuildmat.2023.134533","article-title":"Mechanical and fracture properties of slag\/steel slag-based geopolymer fully recycled aggregate concrete","volume":"413","author":"Zheng","year":"2024","journal-title":"Constr. Build. Mater."},{"key":"10.1016\/j.engappai.2026.115137_bib56","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1016\/j.conbuildmat.2019.03.006","article-title":"Quick image analysis of concrete pore structure based on deep learning","volume":"208","author":"Zhou","year":"2019","journal-title":"Constr. Build. Mater."}],"container-title":["Engineering Applications of Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S095219762601420X?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S095219762601420X?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T06:48:43Z","timestamp":1781592523000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S095219762601420X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":56,"alternative-id":["S095219762601420X"],"URL":"https:\/\/doi.org\/10.1016\/j.engappai.2026.115137","relation":{},"ISSN":["0952-1976"],"issn-type":[{"value":"0952-1976","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Automatic identification method for phase structure of steel slag concrete based on deep learning network of transformer","name":"articletitle","label":"Article Title"},{"value":"Engineering Applications of Artificial Intelligence","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.engappai.2026.115137","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"115137"}}